Array optimisation is critical for improving power performance and reducing infrastructure costs thereby helping enable tidal-stream energy to become a competitive renewable energy source. However, ascertaining an optimal array layout is a highly complex problem, subject to the specific site hydrodynamics characterisation and multiple inter-disciplinary constrains. In this work, we present a novel optimisation approach that combines an analytical-based wake model, FLORIS, with an ocean model, Thetis. The approach is demonstrated with applications of increasing complexity. By utilising the method of analytical wake superposition, the addition or alteration of turbine position does not require re-calculation of the entire flow field, thus allowing the use of simple heuristic techniques to perform optimisation at a fraction of the computational cost of more sophisticated methods. Using a custom condition-based placement algorithm, this methodology is applied to the Pentland Firth for 24 turbines with a rated speed of 3.05 m/s, demonstrating practical implications whilst also considering the temporal variability of the tide. Micro-siting using this technique generated an array 12% more productive on average than a staggered layout, despite flow speeds regularly exceeding the rated value. Performance was further evaluated through assessment of the optimised layout within the ocean model that represents the turbines through a discrete turbine representation.Used iteratively, this methodology could be applied to deliver improved array configurations in a manner that accounts for local hydrodynamic effects.
For tidal-stream energy to become a competitive renewable energy source, clustering multiple turbines into arrays is paramount. Array optimisation is thus critical for achieving maximum power performance and reducing cost of energy. However, ascertaining an optimal array layout is a complex problem, subject to specific site hydrodynamics and multiple inter-disciplinary constraints. In this work, we present a novel optimisation approach that combines an analytical-based wake model, FLORIS, with an ocean model, Thetis. The approach is demonstrated through applications of increasing complexity. By utilising the method of analytical wake superposition, the addition or alteration of turbine position does not require re-calculation of the entire flow field, thus allowing the use of simple heuristic techniques to perform optimisation at a fraction of the computational cost of more sophisticated methods. Using a custom condition-based placement algorithm, this methodology is applied to the Pentland Firth for arrays with turbines of $$3.05\,\hbox {m}/\hbox {s}$$ 3.05 m / s rated speed, demonstrating practical implications whilst considering the temporal variability of the tide. For a 24-turbine array case, micro-siting using this technique delivered an array 15.8% more productive on average than a staggered layout, despite flow speeds regularly exceeding the rated value. Performance was evaluated through assessment of the optimised layout within the ocean model that treats turbines through a discrete turbine representation. Used iteratively, this methodology could deliver improved array configurations in a manner that accounts for local hydrodynamic effects.
Tidal array optimisation is a multifaceted problem that aims at the improvement of an array design's performance, including its overall power yield. Benefits include reductions in investment uncertainty, thus supporting the tidal stream energy industry to reach its potential. Considering the complex, high-energy tidal hydrodynamics at proposed sites, defining an optimal array layout is challenging and remains an active research area. Existing optimisation methodologies can be either computationally untenable or restrictively simplified for practical cases. We present an optimisation approach that combines an analytical-based wake model, FLORIS, with a coastal ocean hydrodynamics model, Thetis. The approach is first demonstrated through idealised steady and transient flow cases to highlight hydrodynamics structures that are overlooked, including spatial complexity, tidal asymmetry, and the practical exploitation of blockage effects.. We thus explore the use of analytical wake superposition in combination with the use of simple heuristic techniques to achieve turbine array optimisation at a fraction of the computational cost of alternative methods. Towards this objective, we designed a custom condition-based placement algorithm. The algorithm is applied to the Pentland Firth, including a case of 24 turbines that follow a power curve constrained by a rated speed of ~3.0 m/s. This case study serves to demonstrate device-specific implications whilst also considering the temporal variability of the tide. Overall, this turbine layout optimisation process is able to deliver an array design that is 12% more productive on average than a staggered layout. Performance was quantified through assessment of the optimised layout using a shallow water equation model which more correctly represents turbines through discrete momentum sink terms.
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